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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"text-align: center\"><a href=\"index.ipynb\">LAMMPS Python Tutorials</a></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example 3: Working with Per-Atom Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Author: [Richard Berger](mailto:richard.berger@outlook.com)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2D circle of particles inside of box with LJ walls"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from lammps import lammps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "L = lammps()\n",
    "cmd = L.cmd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2d circle of particles inside a box with LJ walls\n",
    "import math\n",
    "\n",
    "b = 0\n",
    "x = 50\n",
    "y = 20\n",
    "d = 20\n",
    "\n",
    "# careful not to slam into wall too hard\n",
    "\n",
    "v = 0.3\n",
    "w = 0.08\n",
    "                \n",
    "cmd.units(\"lj\")\n",
    "cmd.dimension(2)\n",
    "cmd.atom_style(\"bond\")\n",
    "cmd.boundary(\"f f p\")\n",
    "\n",
    "cmd.lattice(\"hex\", 0.85)\n",
    "cmd.region(\"box\", \"block\", 0, x, 0, y, -0.5, 0.5)\n",
    "cmd.create_box(1, \"box\", \"bond/types\", 1, \"extra/bond/per/atom\", 6)\n",
    "cmd.region(\"circle\", \"sphere\", d/2.0+1.0, d/2.0/math.sqrt(3.0)+1, 0.0, d/2.0)\n",
    "cmd.create_atoms(1, \"region\", \"circle\")\n",
    "cmd.mass(1, 1.0)\n",
    "\n",
    "cmd.velocity(\"all create 0.5 87287 loop geom\")\n",
    "cmd.velocity(\"all set\", v, w, 0, \"sum yes\")\n",
    "\n",
    "cmd.pair_style(\"lj/cut\", 2.5)\n",
    "cmd.pair_coeff(1, 1, 10.0, 1.0, 2.5)\n",
    "\n",
    "cmd.bond_style(\"harmonic\")\n",
    "cmd.bond_coeff(1, 10.0, 1.2)\n",
    "\n",
    "cmd.create_bonds(\"many\", \"all\", \"all\", 1, 1.0, 1.5)\n",
    "\n",
    "cmd.neighbor(0.3, \"bin\")\n",
    "cmd.neigh_modify(\"delay\", 0, \"every\", 1, \"check yes\")\n",
    "\n",
    "cmd.fix(1, \"all\", \"nve\")\n",
    "\n",
    "cmd.fix(2, \"all wall/lj93 xlo 0.0 1 1 2.5 xhi\", x, \"1 1 2.5\")\n",
    "cmd.fix(3, \"all wall/lj93 ylo 0.0 1 1 2.5 yhi\", y, \"1 1 2.5\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize initial state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "L.ipython.image(zoom=1.8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run simulation and visualize new state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cmd.thermo_style(\"custom step temp epair press\")\n",
    "cmd.thermo(100)\n",
    "output = cmd.run(40000)\n",
    "L.ipython.image(zoom=1.8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Accessing Atom data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "L.numpy.extract_atom(\"x\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "L.numpy.extract_atom(\"id\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "L.numpy.extract_atom(\"v\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "L.numpy.extract_atom(\"f\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "L.numpy.extract_atom(\"type\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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